Land Cover Change Trajectories Research Articles

Between plaza and peak: a montological perspective on verticality and urbanization in highland Peru

Under the influence of concentrated and extended urbanization, Andean cities and the different altitudinal zones of their “hinterlands” are experiencing profound changes in land cover — from the central plazas up to the highest peaks. The complex regional-geographic characteristics of these socioecological systems, such as the vertical complementarity of land use, require a montological perspective on verticality and urbanization: it transcends disciplinary approaches and can be crucial to properly interpret the trajectories of land cover change and formulate hypotheses for future practice-oriented research. Which trajectories of land cover change characterized altitudinal zones of Andean cities and their surroundings over the last three decades? Are there similarities that allow for the formulation of more general hypotheses? Using the Peruvian cases of Cusco and Huaraz, and combining a traditional altitudinal zonation model of land use in Peru with direct field observations and GIS-based analyses of remotely sensed data from 1991, 2001, 2011, and 2021, this study identifies the main trajectories of land cover change in the Quechua (>2300–3500 m), Suni (>3500–4000 m), and Puna (>4000–4800 m) regions — and finds insightful similarities between Cusco and Huaraz: (1) an impressive area of built-up land substitutes grassland in the Quechua, which, following regional altitudinal zonation models, is characterized by irrigated and rain-fed cropland; (2) an unexpected expansion of irrigated cropland takes place in the Suni, which, in theory, often lacks irrigation infrastructure and is mostly used for rain-fed tuber cultivation; and (3) a clear change from “other land” to grassland occurs in the Puna — where grassland is thought to predominate, anyway, since pre-Hispanic times. Hypothesizing that these changes reflect the interplay between speculative fallow, agricultural intensification, and ecological restoration, the results can be read as vertically complementary, local manifestations of concentrated and extended urbanization in a formerly peripheral mountain region of the Global South — and they underscore the need to overcome mental city-mountain dichotomies for a socially inclusive and ecologically balanced Andean development between plaza and peak.

Agricultural fallows are the main driver of natural forest regeneration in Tanzania

Rates and drivers of natural forest regeneration are areas of uncertainty for policy, forest management and climate change mitigation. In this study, the rate of deforestation and the rate and drivers of natural regeneration are described for 56 million hectares of village land in Tanzania, a country undergoing rapid deforestation. To determine the regeneration and deforestation rates, remote sensing (RS) data for 500 randomly selected points were reviewed for a 34 year period from 1987 to 2021 using Google Earth Engine. Over this period, regeneration, involving a transition from forest to non-forest and back to forest was detected on 4.8% of village land (95% CI: 3.1%–7.1%), while 0.8% of land transitioned from non-forest to forest (95% CI: 0.2%–2.04%). 22% of village land was deforested (95% CI: 18.6%–26.1%), equivalent to a mean annual net loss of 0.35 million hectares of forest. Using a combination of RS data, field plots and structured interviews, the land cover change trajectories of 180 regenerating plots, in 10 sampling clusters, were assessed to identify regeneration drivers and assess biomass and tree species accumulation rates. Agricultural fallows are the regeneration driver in 47% of plots (95% CI: 39.8%–54.8%). Other common regeneration drivers include abandonment of cultivated areas for reasons apart from fallowing, conservation and post wood-extraction abandonment in 19% (95% CI: 13.9%–26%), 18.3% (95% CI: 13%–24.8%) and 12.8% (95% CI: 8.3%–18.6%) of plots, respectively. The mean carbon sequestration rate was 1.4 Mg C ha−1 y−1, equivalent to 4.3 Tg C y−1 (95% CI: 3.9–4.7 Tg C y−1) across the 3.15 million hectares of regenerating village land forest. The mean species accumulation rate was 1.08 species y−1 (95% CI: 1.0–1.2). Regeneration time, location and precipitation have the greatest influence on biomass and species richness. The study highlights the potential for natural regeneration to contribute to global and national climate and biodiversity goals and to sustainable, productive forest management. The importance of cooperation and policy-alignment between the forest, agriculture and land sectors are under-scored.

Four decades of urban land cover change in Philadelphia

Given ambitious tree canopy goals, land cover change analyses in cities are imperative. Urban tree canopy change analyses have been hindered by data with low categorical resolution (e.g., canopy vs. not canopy), over relatively short time horizons (5–10 years), representing only two points in time, and scarce linkages to other temporal datasets (e.g., historical socioeconomic data). In this study, using a land cover change data set with five cover classes spanning 40 years (1970–2010) for Philadelphia, PA (US), we asked: which types of land cover changes are most common, and how do those relate to and co-vary with socioeconomic change? Specifically, we tabulated land cover changes (i.e., transition sequences), applied multinomial logistic regression with socioeconomic variables as predictors of land cover change, and used cluster analyses to characterize neighborhood changes associated with land cover change. Land cover stability dominated the transition sequences: the four most common sequences were stable road (e.g. road-road-road-road-road), stable building, tree canopy, and herbaceous vegetation, collectively accounting for 62.57% of all sequences. Multinomial logistic regression identified that increases in homeownership, income, and educational attainment were associated with a higher probability of tree canopy persistence. Cluster analyses via Affinity Propagation showed that some Census tracts have similar land cover change trajectories, and yet different socioeconomic trends. These findings point towards opportunities to focus on tree preservation alongside the importance of establishing new tree canopy through planting. Our study demonstrates the mix of stability and dynamism in multidecadal urban land cover change, and the importance of connecting land cover changes with socioeconomic changes.

Mapping Cropland Abandonment in Mountainous Areas in China Using the Google Earth Engine Platform

Knowledge about the spatial-temporal pattern of cropland abandonment is the premise for the management of abandoned croplands. Traditional mapping approaches of abandoned croplands usually utilize a multi-date classification-based land cover change trajectory. It requires quality training samples for land cover classification at each epoch, which is challenging in regions of smallholder agriculture in the absence of high-resolution imagery. Facing these challenges, a theoretical model is proposed to recognize abandoned croplands based on post-abandonment secondary succession. It applies the continuous change detection and classification (CCDC) temporal segmentation algorithm to Landsat time series (1986~2021) to obtain disjoint segments, representing croplands’ status. The post-abandonment secondary succession showing a greening trend is recognized using NDVI-based harmonic analysis, so as to capture its preceding abandonment. This algorithm is applied to a mountainous area in southwest China, where cropland abandonments are widespread. Validation based on stratified random samples referenced by a vegetation index time series and satellite images shows that the detected abandoned croplands have user accuracy, producer accuracy and an F1 score ranging from 43% to 71%, with variation among abandonment year. The study area has a potential cropland extent of 22,294 km2, within which 9252 km2 of the cropland was abandoned. The three peak years of abandonment were 1994, 2000, and 2011. The algorithm is suitable to be applied to large-scale mapping due to its automatic manner.

A novel multiple change detection approach based on tri-temporal logic-verified change vector analysis in posterior probability space

• TLCVAPS gets rid of the dependence on change class information that contained in training samples, reducing the cost of sample acquisition in multiple change detection problems. • TLCVAPS avoids the error accumulation caused by comparing classification results at different dates for change trajectory detection. • TLCVAPS is the first attempt to introduce temporal logic into multiple change detection tasks, which is a pilot research for the utilization of time information. Detailed land cover change trajectory offers a better opportunity for understanding the dynamic of land surface process. However, change information contained in training samples, which are usually difficult to obtain, needs to be provided in advance to achieve such goal within a complex scenario. A novel multiple change detection approach, namely Tri-temporal Logic-verified Change Vector Analysis (TLCVA) in posterior Probability Space (TLCVAPS), was proposed in this paper. It removes the dependence on change class information contained in training samples, while reducing the detection errors by taking change logic into account for the first time. The proposed approach consists of three steps, including: (1) change vector produced in posterior probability space, (2) binary change detection via TLCVA, and (3) change trajectory identification through combining change vector angle comparison and logic verification in change pattern. We applied the proposed approach on three tri-temporal datasets obtained in Nanjing, Xianning, and Zhenjiang, China, respectively. The results confirmed the superiority of TLCVAPS in comparison with state-of-the-art multiple change detection methods with the same prior knowledge.

ANALYSIS OF LANDCOVER CHANGE AND ITS TRAJECTORY IN SUB-SAHARAN WEST AFRICA

The study analysed land cover change and its trajectory in the study area using 300m CCI-land cover data for three epochs (2000, 2005 and 2010) respectively. Five sampling sites were selected and analysed land cover change trajectories. The findings show a continued decline in closed forest and sparse vegetation and increase in cropland; an indication of land degradation. This pattern of land cover change is accelerated by the increasing number of human populations which is estimated to be growing at the rate of 2-3% in Africa by the year 2100. This nature of population growth is expected to increase the size of croplands to support food security, which will exert more pressure on the ecosystem. However, the land cover trajectories presented in the five sampling points does not portray much changes. This can be attributed partly to the temporal extent of the study (15-years) and the spatial resolution of the data. Overall, the land cover change trajectories in the five sampling sites shows that the major changes in the land cover have been caused by human activities and to some extent natural climatic variations especially along the marginal areas, where the size of bare surface have increased. Therefore, there is a need to carry out a comprehensive land cover assessment at local level to ascertain the major local driving forces and biophysical drivers of land cover degradation in the study area

Coastal Land-Use and Land-Cover Change Trajectories: Are They Sustainable?

In this study, past and current land-use and land-cover (LULC) change trajectories between 1947 and 2018 were analysed in terms of sustainability using a unique set of nine detailed, high-precision LULC thematic maps for the municipality of Portimão (Algarve region), Portugal. Several Geographic Information System (GIS)-based spatial analysis techniques were used to process LULC data and assess the spatiotemporal dynamics of LULC change processes. The dynamics of LULC change were explored by analysing LULC change trajectories. In addition, spatial pattern metrics were introduced to further investigate and quantify the spatial patterns of such LULC change trajectories. The findings show that Portimão has been experiencing complex LULC changes. Nearly 52% of the study area has undergone an LULC change at least once during the 71-year period. The analysis of spatial pattern metrics on LULC change trajectories confirmed the emergence of more complex, dispersed, and fragmented shapes when patches of land were converted from non-built categories into artificial surface categories from 1947 to 2018. The combined analysis of long-term LULC sequences by means of LULC change trajectories and spatial pattern metrics provided useful, actionable, and robust empirical information that can support sustainable spatial planning and smart growth, which is much needed since the results of this study have shown that the pattern of LULC change trajectories in Portimão municipality has been heading towards unsustainability.

Long-term climate-influenced land cover change in discontinuous permafrost peatland complexes

Abstract. The discontinuous permafrost zone is undergoing rapid transformation as a result of unprecedented permafrost thaw brought on by circumpolar climate warming. Rapid warming over recent decades has significantly decreased the area underlain by permafrost in peatland complexes. It has catalysed extensive landscape transitions in the Taiga Plains of northwestern Canada, transforming forest-dominated landscapes to those that are wetland dominated. However, the advanced stages of this landscape transition, and the hydrological and thermal mechanisms and feedbacks governing these environments, are unclear. This study explores the current trajectory of land cover change across a 300 000 km2 region of northwestern Canada's discontinuous permafrost zone by presenting a north–south space-for-time substitution that capitalizes on the region's 600 km latitudinal span. We combine extensive geomatics data across the Taiga Plains with ground-based hydrometeorological measurements collected in the Scotty Creek basin, Northwest Territories, Canada, which is located in the medial latitudes of the Taiga Plains and is undergoing rapid landscape change. These data are used to inform a new conceptual framework of landscape evolution that accounts for the observed patterns of permafrost thaw-induced land cover change and provides a basis for predicting future changes. Permafrost thaw-induced changes in hydrology promote partial drainage and drying of collapse scar wetlands, leading to areas of afforestation forming treed wetlands without underlying permafrost. Across the north–south latitudinal gradient spanning the Taiga Plains, relatively undisturbed forested plateau–wetland complexes dominate the region's higher latitudes, forest–wetland patchwork are most prevalent at the medial latitudes, and forested peatlands are increasingly present across lower latitudes. This trend reflects the progression of wetland transition occurring locally in the plateau–wetland complexes of the Scotty Creek basin and informs our understanding of the anticipated trajectory of change in the discontinuous permafrost zone.

Potentials of Protected Areas as Carbon sinks and Implication on Climate Change in Cameroon

Cameroon has 115 000 km2 land area designated as Protected Areas (PAs), providing society with many ecosystem services including climate change mitigation. The study was aimed at examining the potentials of inland and coastal PAs as carbon sinks and implication on climate change mitigation in Cameroon between 1978 and 2014. Data for the study was obtained from both primary and secondary sources. Remote Sensing and Geographic Information System (GIS) techniques were used in the analysis of satellite imageries. The land cover change trajectory revealed a drop in the rate of conversion of dense forest within inland PAs compared to coastal PAs. Results reveaked carbon sequestration within inland PAs between 1978 and 2014 and the PAs were able to absorb166,590.73 tonnes/ha CO2 from the atmosphere and build up carbon resulting to the amelioration of the local and regional climate of the area with a positive impact on global climate change. Within the coastal PAs, there was 71,418.48 tonnes/ha CO2 emission through 1978 – 2014 with resulting negative impacts on the climate. The constraints to effective PA management identified were human and capital resource problems, hostility of the local population, delayance in law enforcement and poverty. To ensure their roles in climate moderation there should be a better forest policy implementation within PAs in Cameroon by making available more capital and human resources to PAs management to enable them cope in the face of growing anthropogenic threats.

Land Cover and Land Use Change Trajectory Hopping Facilitates Estate Crop Expansion into Protected Forests in Indonesia

Land Cover and Land Use Change Trajectory Hopping Facilitates Estate Crop Expansion into Protected Forests in Indonesia

Applying spatial autocorrelation and logistic regression to analyze land cover change trajectory in a forested watershed

Applying spatial autocorrelation and logistic regression to analyze land cover change trajectory in a forested watershed

Continuous Monitoring of Urban Land Cover Change Trajectories with Landsat Time Series and LandTrendr-Google Earth Engine Cloud Computing

Producing accurate land cover maps is time-consuming and estimating land cover changes between two generated maps is affected by error propagation. The increased availability of analysis-ready Earth Observation (EO) data and the access to big data analytics capabilities on Google Earth Engine (GEE) have opened the opportunities for continuous monitoring of environment changing patterns. This research proposed a framework for analyzing urban land cover change trajectories based on Landsat time series and LandTrendr, a well-known spectral-temporal segmentation algorithm for land-based disturbance and recovery detection. The framework involved the use of baseline land cover maps generated at the beginning and at the end of the considered time interval and proposed a new approach to merge the LandTrendr results using multiple indices for reconstructing dense annual land cover maps within the considered period. A supervised support vector machine (SVM) classification was first performed on the two Landsat scenes, respectively, acquired in 1987 and 2019 over Kigali, Rwanda. The resulting land cover maps were then imported in the GEE platform and used to label the interannual LandTrendr-derived changes. The changes in duration, year, and magnitude of land cover disturbance were derived from six different indices/bands using the LandTrendr algorithm. The interannual change LandTrendr results were then combined using a robust estimation procedure based on principal component analysis (PCA) for reconstructing the annual land cover change maps. The produced yearly land cover maps were assessed using validation data and the GEE-based Area Estimation and Accuracy Assessment (Area2) application. The results were used to study the Kigali’s urbanization in the last three decades since 1987. The results illustrated that from 1987 to 1998, the urbanization was characterized by slow development, with less than a 2% annual growth rate. The post-conflict period was characterized by accelerated urbanization, with a 4.5% annual growth rate, particularly from 2004 onwards due to migration flows and investment promotion in the construction industry. The five-year interval analysis from 1990 to 2019 revealed that impervious surfaces increased from 4233.5 to 12116 hectares, with a 3.7% average annual growth rate. The proposed scheme was found to be cost-effective and useful for continuously monitoring the complex urban land cover dynamics, especially in environments with EO data affordability issues, and in data-sparse regions.

A spatiotemporal structural graph for characterizing land cover changes

ABSTRACT Characterizing landscape patterns and revealing their underlying processes are critical for studying climate change and environmental problems. Previous methods for mapping land cover changes largely focused on the classification of remote sensing images. Therefore, they could not provide information about the evolutionary process of land cover changes. In this paper, we developed a spatiotemporal structural graph (STSG) technique for a comprehensive analysis of land cover changes. First, a land cover neighborhood graph was generated for each snapshot to quantify the spatial relationship between adjacent land cover objects. Then, an object-based temporal tracking algorithm was designed to monitor the temporal changes between land cover objects over time. Finally, land cover evolutionary trajectories, pixel-level land cover change trajectories, and node-wise connectivity changes over time were characterized. We applied the proposed method to analyze land cover changes in Suffolk County, New York from 1996 to 2010. The results demonstrated that STSG can not only characterize and visualize detailed land cover changes spatially but also maintain the temporal sequence and relations of land cover objects in an integrated space-time environment. The proposed STSG provides a useful framework for analyzing land cover changes and can be adapted to characterize and quantify other spatiotemporal phenomena.

Impact of Land-cover Change Trajectories on Water Cycle Dynamics in the Jing-Jin-Ji Region, China, from 2000 to 2015

ABSTRACT Diao, W.; Zhao, Y.; Zhai, J.; He, F.; Wang, Q., and He, G., 2019. Impact of land cover change trajectories on water cycle dynamics in the Jing-Jin-Ji region, China, from 2000 to 2015. In: ...

Trajectories of land cover transformation in zonal types of landscapes of Indochina

The article deals with the study of the land cover change of Indochina based on the MODIS Land Cover database for 2001—2012. Geospatial land cover data, which are objectively recorded land surface characteristics, are widely used for small-scale mapping of landscapes and ecological systems. The case region of Indochina was selected for the analysis of land cover transformation. In recent decades it has been undergoing active transformation of land use, associated with rapid economic development, substantial population growth, and reorientation of the agricultural sector to foreign markets. The processes of land cover change were studied within the boundaries of zonal types of landscapes, altitudinal zonality spectra, and groups of intrazonal landscapes. The density of changes is uneven in different zonal types of landscapes, the greatest range of transformations is characteristic to the deciduous monsoon forests, semi-evergreen forests (in the subequatorial belt), and within river valleys. The main trajectories of land cover change for 2001—2012 are as follows: 1) expansion of arable areas due to the reduction of forests, savannas and grasslands; 2) the likely increase in the area of perennial plantations (mainly rubber trees and oil palm); 3) forest degradation and spread of savannas; 4) fluctuations of land under shifting cultivation. Since the 2000s commercial production of perennial cash crops is the main cause of deforestation in the region. Land clearing for these needs could have a greater impact on forest cover than logging. The revealed features of land cover change for Indochina made it possible to specify the regional characteristics of the transformation processes as compared to global typology of land coverchanges.

Critical Zone Science in the Anthropocene: Opportunities for biogeographic and ecological theory and praxis to drive earth science integration

Critical Zone Science (CZS) represents a powerful confluence of research agendas, tools, and techniques for examining the complex interactions between biotic and abiotic factors located at the interface of the Earth’s surface and shallow subsurface. Earth’s Critical Zone houses and sustains terrestrial life, and its interacting subsystems drive macroecological patterns and processes at a variety of spatial scales. Despite the analytical power of CZS to understand and characterize complicated rate-dependent processes, CZS has done less to capture the effects of disturbance and anthropogenic influences on Critical Zone processes, although some Critical Zone Observatories focus on disturbance and regeneration. Methodological approaches from biogeography and ecology show promise for providing Critical Zone researchers with tools for incorporating the effects of ecological and anthropogenic disturbance into fine-grained studies of important Earth processes. Similarly, mechanistic insights from CZS can inform biogeographical and ecological interpretations of pattern and process that operate over extensive spatial and temporal scales. In this paper, we illustrate the potential for productive nexus opportunities between CZS, biogeography, and ecology through use of an integrated model of energy and mass flow through various subsystems of the Earth’s Critical Zone. As human-induced effects on biotic and abiotic components of global ecosystems accelerate in the Anthropocene, we argue that the long temporal and broad spatial scales traditionally studied in biogeography can be constructively combined with the quantifiable processes of energy and mass transfer through the Critical Zone to answer pressing questions about future trajectories of land cover change, post-disturbance recovery, climate change impacts, and urban hydrology and ecology.

Monitoring Effects of Land Cover Change on Biophysical Drivers in Rangelands Using Albedo

This paper explores the relationship between land cover change and albedo, recognized as a regulating ecosystems service. Trends and relationships between land cover change and surface albedo were quantified to characterise catchment water and carbon fluxes, through respectively evapotranspiration (ET) and net primary production (NPP). Moderate resolution imaging spectroradiometer (MODIS) and Landsat satellite data were used to describe trends at catchment and land cover change trajectory level. Peak season albedo was computed to reduce seasonal effects. Different trends were found depending on catchment land management practices, and satellite data used. Although not statistically significant, albedo, NPP, ET and normalised difference vegetation index (NDVI) were all correlated with rainfall. In both catchments, NPP, ET and NDVI showed a weak negative trend, while albedo showed a weak positive trend. Modelled land cover change was used to calculate future carbon storage and water use, with a decrease in catchment carbon storage and water use computed. Grassland, a dominant dormant land cover class, was targeted for land cover change by woody encroachment and afforestation, causing a decrease in albedo, while urbanisation and cultivation caused an increase in albedo. Land cover map error of fragmented transition classes and the mixed pixel effect, affected results, suggesting use of higher-resolution imagery for NPP and ET and albedo as a proxy for land cover.

Impact of land cover change on ecosystem service supply in mountain systems: a case study in the Cantabrian Mountains (NW of Spain)

Land abandonment and the loss of traditional farming practices are thought to control land cover dynamics, and hence the ecosystem service supply in traditionally managed mountain landscapes. We evaluate the impact of land cover changes in Cantabrian Mountains (NW Spain), over 1990–2012, on the potential supply capacity of ecosystem services (regulating, provisioning, and cultural) at both regional and local scales. We also analyze trends in the use of ecosystem services at the local scale. Land cover changes were estimated from CORINE Land Cover database. Patterns of potential ecosystem service supply were assessed by applying an ecosystem service supply capacity matrix and trends in their actual use by using field data. Main trajectories of land cover change encompassed woody vegetation spread in semi-natural open systems and agricultural expansion in the most suitable areas. The capacity of landscape to provide ecosystem services improved during 1990–2012 at both scales. We detected trade-offs between the potential supply of ecosystem services associated to natural systems and those linked to traditional land uses, at both regional and local scales. Changes in the potential supply of ecosystem services matched trends in ecosystem service use. This study could help develop future scenarios to address upcoming challenges in ecosystem service supply.

Analyses of Land Cover Change Trajectories Leading to Tropical Forest Loss: Illustrated for the West Kutai and Mahakam Ulu Districts, East Kalimantan, Indonesia

In Indonesia, land cover change for agriculture and mining is threatening tropical forests, biodiversity and ecosystem services. However, land cover change is highly dynamic and complex and varies over time and space. In this study, we combined Landsat-based land cover (change) mapping, pixel-to-pixel cross tabulations and expert knowledge to analyze land cover change and forest loss in the West Kutai and Mahakam Ulu districts in East Kalimantan from 1990–2009. We found that about one-third of the study area changed in 1990–2009 and that the different types of land cover changes in the study area increased and involved more diverse and characteristic trajectories in 2000–2009, compared to 1990–2000. Degradation to more open forest types was dominant, and forest was mostly lost due to trajectories that involved deforestation to grasslands and shrubs (~17%), and to a lesser extent due to trajectories from forest to mining and agriculture (11%). Trajectories from forest to small-scale mixed cropland and smallholder rubber occurred more frequently than trajectories to large-scale oil palm or pulpwood plantations; however, the latter increased over time. About 11% of total land cover change involved multiple-step trajectories and thus “intermediate” land cover types. The combined trajectory analysis in this paper thus contributes to a more comprehensive analysis of land cover change and the drivers of forest loss, which is essential to improve future land cover projections and to support spatial planning.

Degradation monitoring in Silvo-pastoral systems: A case study of the Mediterranean region of Turkey

To identify policies that will promote positive effects and mitigate negative ones of grazing is a major challenge in the Silvo-pastoral system. This paper presents the role of examining land-cover change trajectories by remote sensing imagery in grazing policy monitoring. The study was conducted for Duzlercami forest ecosystem located in the Mediterranean geographical region of Turkey and administrated by the General Directorate of Forestry (GDF) of the Ministry of Forestry and Water Affairs. Time series land-cover datasets from Landsat images between 1988 and 2016 were collected and classified. To link the conversions among trajectories and grazing policy, class level landscape metrics derived from the classified images were used. To validate the approach, yearly grazing-plans managed by GDF and populations of livestock were used. Results of this research have indicated that even though there is a yearly grazing plan, overgrazing can happen on the pilot site, and it can be easily identified by the destruction of woody vegetation. The notable correlation (r2 = 0.89) between degraded woody vegetation and cattle population has occurred in the last 30 years in the landscape, and Landsat imagery can effectively support the grazing policy mapping and monitoring.